The field of the invention relates generally to computer-implemented programs and, more particularly, to a computer-implemented method and system for determining fleet conditions and operational management thereof.
Asset management generally refers to the combination of engineering, financial, economic, logistical, and other practices applied to a group of physical assets with the objective of providing the required level of service in the most cost-effective manner. It includes the management of the whole life cycle of an asset. This includes design, construction, commissioning, operating, maintaining, repairing, modifying, replacing, decommissioning, and disposal of physical and infrastructure assets. Effective operation and maintenance of assets in a constrained budget environment require some sort of prioritization scheme.
Many known prioritization schemes have employed a time-based paradigm. In such time-based paradigms, asset management is conducted according to a schedule that enhances the availability of replacement parts and human capital to service assets. Such time-based paradigms assume particular life-spans of assets and asset components and accordingly attempt to prioritize the service and replacement of assets and asset components based upon these assumed life-spans. The time-based paradigm was popular, especially with large groupings of assets, due to the significant costs associated with inspection of assets for variance. The benefits of individualized asset management were outweighed by burdens of individual inspections and an unpredictable repair, maintenance, and replacement scheme.
A significant problem with the time-based paradigm is that the assets and asset components may be serviced or replaced prematurely, resulting in sub-optimal physical and human capital investment. Assets and asset components serviced in a time-based paradigm run the risk of unnecessary resource use. For example, the time-based paradigm will cause some assets and asset components to be retired prematurely, and therefore lose asset value in terms of remaining useful life.
Recently, there has been a shift from time-based paradigms to condition-based paradigms. In many known condition-based paradigms, the asset conditions are monitored and assets are flagged or noted for diagnostics, repair, or replacement at the time that the individual asset or asset component requires it based upon measured variances from established parameters. Many such known condition-based paradigms have created logistics problems for fleet management programs. Since the scheduling of diagnostics, repair, or replacement in a condition-based paradigm is dynamic and asynchronous, i.e., assets are scheduled without knowledge of the scheduling of other assets, predictability may suffer. In a time-based paradigm, a known repair schedule may allow for a relatively stable allocation of human resources and inventory. The condition-based paradigm lacks such a schedule, causing variability in asset operation and conditions, in turn causing variability in required human resources and required asset inventory.
This makes fleet management more complex, since there are interdependencies in the demands placed by the various assets on the logistics infrastructure. In a time-based paradigm, these interdependencies can be factored into decision-making due to the relatively stable and static nature of the model. With condition-based paradigms, it becomes harder to account for the interdependencies without looking at the condition of the entire fleet, i.e., in condition-based paradigms, the state of the fleet and information related to it can change quickly and dynamically.